Andy fisher

© 2013 Merkle Inc. All Rights Reserved. Confidential
1
Analytics Trends from the Trenches
Not Really Magic –
Secrets of real time
Personalization and
Attribution

2
The Customer Relationship Marketing Agency
POS Phone Site Mobile TV Radio Display Print Social
Direct
mail Email Search
Integrating diverse capabilities
Through optimizing customer touchpoints
Life sciencesNonprofit| ||
Increased customer value Improved media effectivenessImproved marketing ROI| |
CRM Outcomes
Integrating diverse capabilities
Consulting Technology Experience, creation & digital mediaData & analytics| | |
Utilizing industry experience to drive strategy
Delivered across multiple engagement types
Consulting | Marketing services | Agency of record
Life sciencesRetail banking &
Consumer finance
Media &
entertainment
Technology
& B2B
Nonprofit
Insurance & wealth
management
| | | || Retail |

3
Merkle Company Overview
• Bronze Stevie Award “Business to Business Marketing
Campaign of the Year- Business Services” „13
• Ad Age A-List: “Agency to Watch in 2012”
• Largest privately-held agency in U.S., Ad Age ‟12
• 6th Largest CRM/Direct Marketing Agency, Ad Age ‟12
• Recognized by SmartCEO Magazine as a Future 50
Company „11
• NCDM Awards ‟04, ‟05, ‟06, ‟09, ‟10, „11
• Recognized by Forrester ‟03, „06, ‟07 &‟10
• Multiple MAXI Award Winner ‟10 ‟11
• Multiple DMA Innovation Award Winner „10
Distinctive experience Extraordinary expertise
Sustained 25% growth since 1989 Awarded and recognized
Revenueinmillions
• Privately held by current management since 1988
• 150+ world class clients
• Manage over 140 marketing databases
• Manage 1.6+ petabytes of customer data
• Inform over $10 billion marketing decisions annually
• 1,700+ Employees
• 250+ advanced degreed statisticians
• 300+ dedicated digital professionals
• 500+ marketing technology professionals
• 100+ creative professionals
$148
$180
$211 $223
$255
$303
$320
$365
$50
$100
$150
$200
$250
$300
$350
$400
2006 2007 2008 2009 2010 2011 2012 2013E

4
We Wrote a Book – for Analysts by Analysts
Focus on HOW you bring customer-centric data, infrastructure and analytics to digital
What‟s Possible and not Possible
Anonymous/Known Profile Data
Channel Specific Data Source issues
Client Examples
70+ Analysts Contributed
The realities of making this happen
I‟m here to share some of the Trends I saw with you…

5
3% 14% 3% 5% 5% 5% 15% 5% 5% 40%
30% 40% 30%
Attribution: The Theory – but how to handle non-addressable?
Day 8-30 Day 1-7 Day 0-1
New
Customer
Actual
experience
Customer clicks paid
search, so search gets credit
Search over-attributed
Direct
Consumer clicked on search
link. Rules: TV and DM
exposure possible in last 7
days, so assign credit
Better but still not accurate
Rules Based
Modeled
Model-adjusted interaction
Most accurate
$
TV viewDirect mail sent Newspaper view Display view Social visitWebsite visit Paid search click
Mass and Offline Digital
5
100%

6
Historically non-addressable media has been valued with MMO
Time
0
50
100
150
200
250
300
350
0 5 10 15 20 25 30
Time
TV
0
200
400
600
800
1000
1200
0 5 10 15 20 25 30
Time
Direct Mail
0
50
100
150
200
250
0 5 10 15 20 25 30
Time
Radio
Input Data
• Relevant data collected to
incl. paid media & external
influencers
• Data is transformed to
account for 2 key concepts :
1.Adstock – media
exposure has a lasting
impact over time
2.Saturation – there are
upper limits for response
(leads, apps, etc.)
0
10
20
30
40
50
60
1 3 5 7 9 11 13 15 17 19 21 23
Revenue
Time
Sales Decomposition
TV
Direct Mail
Radio
Print
Base
Statistical Models
Base
51%
Print
14%Radio
8%
Direct Mail
11%
TV
16%
Segment 1
p
i
t
p
itit
i
xy
1
-
100
200
300
400
500
600
Segment 1 Segment 2
280 298
73 73
42 46
62 49
87 71
Revenue
TV
Direct Mail
Radio
Print
Base
Statistical Models
• Econometric
methodology based on
statistical and economic
theory
• Most basic model is
multiple regression using
OLS (Ordinary Least
Squares)
• Model sophistication
rapidly advances to solve
problems in data or
estimation
Investment
0
20
40
60
80
100
120
140
160
180
200
0.0 24.0 48.0
IncrementalRevenue
Investment Amount
Print
Radio
Direct Mail
TV
0
20
40
60
80
100
120
140
160
180
200
0.0 24.0 48.0
IncrementalRevenue
Investment Amount
Print
Radio
Direct Mail
TV
Response Curves &
Optimization
• Estimated coefficients from
model are used to simulate
response at every input
level, giving a response
curve
• Optimizations are based on
the concept of Marginal
Return on
Investment, which comes
from the response curve

7
Trend 1: Top Down MMO and Bottom Up Attribution Merge
Display
$60
Video
$80
Search
$91
Other
$113
LG 1 - $190Video 1 - $121
Video 2 - $35
Video 3 - $213
Video 4 - $23
Video 5 - $8
Video 6 - $4
Search 1 - $115
Search 2 - $87
Search 3 - $39
LG 2 - $163
LG 3 - $87
LG 4 - $74
LG 5 - $32
LG 6 - $29
LG 7- $11
Remarketing - $12
Guaranteed - $80
Non-guaranteed - $30
Auto / insurance - $18
National media
(TV & radio)
$140
Local media
(TV & radio)
$200
Direct mail
$180
Digital
$83Mix
Digital
Attribution
Top down
Bottom up
Digital Attribution and Marketing Mix Modeling are unified into one version of truth.
$
Sales

8
Reality Check
MMO + Attribution
• Media Mix Optimization together with Attribution
• One model
• Integrates Offline and Online
• Most vendors doing some form of this
• Historically the two are related
Better Math X-Channel experts
Attribution gaps
• Incrementality
• Decay Factors
• Interplay of media
• Data Scientists
• All channel data
• Data Viz Experts
• Hard to find
To do this well you need
Data Quality – Cooke Data has Issues
• Idea 1: Leverage CRM data
• Idea 2: Leverage Panels/”Good” samples
• Idea 3: Statistical Identification/Fingerprinting
• Idea 4: Model Cookie Deletion
• Idea 5: First Party Data
• No Silver bullet
Lack of Validation
• Rare in MMO
• Very rare in
Attribution
• No agreed upon
methodology
Open Issues
Social Challenges
• Predicitvity
• Models
• Sentiment
Problems

9
The future: MMO/Attribution becomes segment based
Display
$60
Video
$80
Search
$91
Other
$113
LG 1 - $190Video 1 - $121
Video 2 - $35
Video 3 - $213
Video 4 - $23
Video 5 - $8
Video 6 - $4
Search 1 - $115
Search 2 - $87
Search 3 - $39
LG 2 - $163
LG 3 - $87
LG 4 - $74
LG 5 - $32
LG 6 - $29
LG 7- $11
Remarketing - $12
Guaranteed - $80
Non-guaranteed - $30
Auto / insurance - $18
National media
(TV & radio)
$140
Local media
(TV & radio)
$200
Direct mail
$180
Digital
$83
Measurement and
Calibration by
Segment
Mix
Digital
Attribution
Segment 1 Segment 2 Segment 3
Top down
Bottom up
Starting in some verticals (i.e. Life Sciences). Huge opportunity for people here.

10
Personalization: If I solve for identity and experience, I can …
Understand whom I am
speaking with
Personalize and optimize
the experience
Attribute the behaviors
Movers &
Shakers
Family
Matters
Mature
Planners
Passives
Loners

11
Trend 2: Cross-channel personalization
AgentDigital
Media
Search
Sales force automation
/ call planning
prioritized by agent‟s
segment and value mix
Served Fixed Income X-sell offer
Increased bid amount on
“retirement planning”
Increased Sales Force ProspectingCreative selection
Site
For display, optimization
output is directly fed to
the Demand Side
Platform
Decisioning
Optimization
Feed
For SEM, bidding engine
weights are output of
analytics correlating keyword
to high-value segments
For site, real-time
integration of segments
into offer management
system

12
Reality Check
Many people doing within channel personalization well
Far fewer are doing x-Channel personalization
Cross Channel Infrastructure
• Data source across channels
• Enterprise segmentation
• Cross channel Technology
• Within-channel activation
• The technology is good enough
To do this well you need
Organizational Silos
• Different Goals
• Different notion of customer
• Lack of incentive
• Different measurement approaches
Open Issues
Think this will become a large practice moving forward
Big opportunity for people in the room

13
A few More Trends Worth Mentioning…

14
Trend 3: Consistent Segmentation Across the Enterprise
Multiple segmentations across media, site, CRM, research, etc all become one
Strategic Tactical
• Based on behavior
• Actionable; tied to database
• Informs tactics
• Based on research
• Rich insight into attitudes
• Informs strategy
Rich Actionable
Strategic
Planning
Value
Proposition
Program
Planning
Addressable
Media
Big opportunity from programmatic techniques to become the activation layer.

15
Trend 4: More Data in Connected CRM Platform (cDMP)
Identifiable
Platform (CRM)
Targeting & Personalization
cR
TV Print Radio CCDM EM Display Search Social Mobile SiteRetail
Aggregate
Media Platform
Digital Data
Management
Platform
First, Second and Third Party Data Sources
Integrated attribution and
targeting accessible in real-time
All anonymous and known digital
exposures keyed to a universal
user key (cookie level)
Connected Recognition (cR) links known
consumers (and their value) to their media interactions in
the anonymous marketplace – mass and digital
Foundational view of the prospect and
customer including
segmentation, contact history, and
value
All offline media interactions mapped
to the individual/HH level including
media research panel data
Segmentation
Measurement & Attribution
Consumer Event Stream

16
Data Explosion “Big Data” is
complex
Need for
multiple
sources
Change in
what’s
valuable
Increase of data
sources, digital, frag
mentation, and
overall volume of
data in unlike any
other time in the
industry
“Big Data” is
driving big
confusion; not
always translating
into insights
No single provider
of data can do it all
- there are plenty
of data sources
out there, but no
single source can
have all the
answers
“Smart Data” is not
a commodity
Increased focus on
consumer
preference and
data privacy
Privacy
Trend 5: Fragmentation and Confusion in the Data World
A POV: The industry needs validation services.

17
Trend 6: Business Savvy Statisticians -> Data Scientists
HR Manager: I used to look for unicorns – now I need purple unicorns
All good new for the analytics community. But it will change how we do business.
Data
Scientists
Big Data Tech:
Hadoop, Hive, Pi
g, Python, Mongo
, Data Viz, etc
Stat. Expertise:
Modeling, Math, S
AS, R, scientific, d
eep data source
knowledge etc
Business Acumen:
Communication, Pre
sentation, MBA, cons
ulting etc
Academia Organization
• How to train?
• What department?
• Many Universities
trying experiments
• Many self-taught
• How to hire/create?
• How to incent?
• Analysts rise in org
•CMOs
•CTOs
Business Model The Big Question
• Costs rise
• New models form
• Some exit
•Outsourcing wage
gap closing
• What happens
when these people
manage traditional
media buys?

18
Andy Fisher
Chief Analytics Officer
410.794.7036
alfisher@merkleinc.com
Questions?

Andy fisher

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